Causal Effects via Propensity Scores

How to estimate effects from observational data

This article is the 2nd post in a series on causal effects. In the previous post, we laid a theoretical foundation for causal effects, but there were some lingering practical concerns. Namely, how can we compute causal effects from observational data? Here, I will discuss a set of techniques that do exactly this using something called a propensity score. The discussion will be followed up with example Python code of using these techniques with real-world data.